JOU RN AL O F GEOPHYS ICA L RESEARC H , VOL. 11 7, DI 92 09, d oi:JO, 10291201 2JDOI8056 , 2012

Influence of desert dust intrusions on ground-based and satellite­derived ultraviolet irradiance in southeastern Spain

M . Anton, I A. Valenzuela,2,3 R. Roman ,4 H. Lyamani,2 ,3 N . Krotkov,5 A. Arola,6

F.1. Olmo,2,3 and L. Alados-Arboledas2,3

Rece ived 8 May 20 12; rev ised 30 August 201 2; accepted 6 September 20 12; publi shed 9 October 20 12.

[I] The desert dust aerosols strongly affect propagation of solar radiation through the atmosphere, reducing surface irradiance available for photochemistry and photosynthesis. This paper evaluates effects of desert dust on surface UV erythemal irradiance (UVER), as measured by a ground-based broadband UV radiometer and retrieved from the satellite Ozone Monitoring Instrument (aMI) at Granada (southern Spain) from January 2006 to December 2010. The dust effects are characteri zed by the transmittance ra tio of the measured UVER to the corresponding modeled clear sky value. The transmittance has an exponential dependency on aerosol optical depth (AOD), w ith minimum values of rvO.6 (attenuation of rv40%). The OMl UVER algorithm does not account for UV aeroso l absorption, which results in overestimation of the ground-based UVER especia lly during dust episodes with a mean relative difference up to 40% . The application of aerosol

. absorption post-correction method reduces aMI bias up to "" 13%. The results highlight great effect of desert dust on the surface UV irradiance in reg ions like southern Spain, where dust intrusions from Sahara region are very frequent.

Citation: Anton, M ., A. Valenzuela, R . Ro man, H . Lyamani , N. Kro tko v, A . Aro la, F. 1. O lmo, and L. A lad os-Arbo ledas (20 12),

Influence o f desert dust in trusions on g round-based and sate llite-derived ul trav io let irradi ance in so utheastern Spai n, J Geophys. Res., 117, 0 19209, doi:10.1029/20 12JDO I8056.

1. Introduction

[2] Mineral dust aerosol pJays an important role in E311h 's climate system, absorbing solar and thermal radiation and modulating Earth 's radi ative budget. The main sources of mineral dust are the deselt areas, with the Sahara being the most important source in the nOlihem hemisphere [Prosp ero et at. , 2002; Ginoux et aI. , 2004; Papayannis et aI. , 2005; Liu et aI. , 2008]. Air masses loaded with Saharan dust particles frequently reach Spanish and Portuguese regions. Several studies analyzed Sah31'an dust contribution to ambient levels of suspended pru1iculate matter, studying the synoptic meteorological conditions responsible for the tran port of tile dust air masses [Rodriguez et aI. , 200 I ; Escudero et aI. , 2005, 2006; Querol et al., 2009]. Other studies focu ed on the retrievals of micro-phys ica l and optical properties of

IDcpartamcnto de Fisica, Univcrsidad dc Extrcmadura, Badajoz, Spain. 2DepartamenlO de Fisica Apli cada, Uni vers idad de Granada, Granada,

Spain . 3Centro Anda luz de Medio Ambiente, Universidad de Granada,

Granada, Spain . 4Depal1amento de Fisica Aplicada, Uni versidad de Vall adoli d,

Va lladolid , Spain. 5Laboratory of Atmospheri c Chemistly and Dynamics, NASA Goddard

Space Flight Center, Greenbelt, Maryland, USA, 6Finnish Meteorological Institute, Kuopio, Fin land.

COITesponding author: M. Anton, Departamento de Fisica, Universidad de Extremadura, ES-06071 Badajoz, Spain . (mananton@unex .es)

1920 12. American Geophysica l Union, All R ights Reserved. 0148-022711 2/20 12JDO 18056

Saharan dust using passive remote sensing measmements with sun-sky photometers [Alados-Arboledas et aI. , 2003, 2008; Lyamani et aI. , 2004, 2005, 2010; Elias etal. , 2006; Toledano el aI. , 2007; Cachorro el 01. , 2008; Prats el aI. , 2008; Wagner et a t. , 2009; Valenzuela el at., 201 2a, 20 12b]. Lidar systems have also been used to characterize the vertical profile and structure of desert dust plumes [Perez el at. , 2006; Guerrero­Rascado el aI. , 2008, 2009; Cordoba-l abonero et al. , 2011 ; PreijJler el ai" 20 11] ,

[3] However, there are relatively few studies analyzing effects of dust intrusions on shortwave solar radiation reaching the Earth 's surface. [Dfaz et aI. , 2001 ; Lyamani et aI. , 2006; Santos et 01. , 2008; Cachorro et aI. , 2008; Anton et aI. , 2012a]. To our knowledge, onl y Diaz et al. [2007] and Anton et al. [20 12b] have analyzed the atmospheric aerosol effects on spectra l UV inadiance during two Saharan dust events in South Spain. In general, there are only a few works about this subject in li terature [e.g. , di Sarra et al., 2002; Meloni et aI. , 2003; Kafashnikova et aI. , 2007; Garcia et aI. , 2009] due to the scarcity of routinely operational ground-based stations with high-qual ity instnullentation to measure simultaneously UV inacliance and aerosol data during desel1 dust intrusions.

[4] The analys is of the di verse atmospheric fac tors affecting the UV irradiance is moti vateq by the harmful effects of thi s radiation on human health, ecosystems, and materials [DifJey, 1991 , 2004]. This paper focuses on the analysis of the influence of dese11 dust aerosol on the UV elythemally weighted surface ilTadi ance (UVER) measured at Granada, a non-industrialized medium-sized city in

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DI9209 ANT6N ET AL.: DESERT DUST EFFECTS ON UV lRRADl ANCE DI9209

southeastern Spain . The study analyzes desert dust intn.l­sions detected during a period from January 2006 to December 2010 to evaluate the differences between the UVER measurements and the satellite retrievals from Ozone Monitoring Instrument (OMI) on NASA EOS Aura satellite [Tanskanen et aI. , 2007]. Previously, largest differences between the satellite and ground-based UV ilTadiance data were reported in urban polluted areas, w ith elevated levels of UV -absorbing aerosols [McKenzie et aI. , 200 I; Kazantzidis et aI. , 2006; Tanskanen et aI. , 2007; l alongo et al. , 2008; Buchard et aI. , 2008]. Thus, it is expected that desert dust particles (with significant absorption in the UV spectral range) will also produce large differences between the sat­ellite-derived and surface measured UV irradiance [e.g., Anton el aI., 2012b].

[5] The article has been organized as follows: Section 2 describes the instruments and data used in this study. Section 3 explains methodology, Section 4 discusses results and section 5 summarizes main conclusions.

2. Instruments and Data

2.1. Ground-Based Measurements [6] The experimental data used ill this study have been

collected at the radiometri c station located on the rooftop of the Andalusian Center for Environmental Studies (CEAMA, 37 .17°N, 3.6 10W, 680 m a.s.1.) in Granada, southeastern Spain. This station is operated by the Atmospheric Physic Group (GFAT) of the Granada University .

[7] A broadband UV radiometer, model UVB-l , manu­factured by Yankee Environmental Systems, Inc. (Massa­chusetts, U.S.), measures spectra lly integrated UV irradiallce weighted with the erythemal action spectrum adopted by the Commission Intemationale de I , Ecla irage (CrE) [McKinlay and DifJey, 1987] (denoted as UVER). Measurements were sampled every ten seconds and recorded as one minute mean voltages on Campbell CRlOX data acqui sition systems. Output voltages are converted into UYER values applying the calibration factors derived from two calibrat ion cam­paigns of broadband UV radiometers at the "El Arenos il1o" TNT A station in Huelva (Spa in) in September 2007 and June 20 11 [Vilaplana el aI. , 2009]. These calibrations included spectral and angular characterization of the instruments and their abso lute calibrati on, performed through the outdoor intercomprui son with a reference Brewer spectroradiometer. Output voltages recorded by the UVB-J radiometer were converted to UVER data applying conversion factors obtai ned from the "two-steps" calibration method [Seckmeyer et aI. , 1997; Webb et al., 2006]. Anton et af. [20 Il a] compared the UVER data provided by the UVB-I radiometer installed in Granada with ramative transfer model calculatio ns for a cloudless sky; their resul ts have shown bigh qua li ty of the UVER data used in this paper.

[8] The ground-based station is also equipped with a CM-II pyranometer for measurements of global olar ilTadi­ance from 0.305 to 2.8 11m. Tllis instmment is fully compliant with the highest ISO perfOlmance criteli a with estimated rel­ative uncertainty better thrul 2% [Kratzenberg et aI. , 2006]. The stability of the pyranometer 's calibrat ion has been peri­odically verified using a reference CM-Il instrument located at the study station and used only for inter-comparison purposes. The calibration fac tors showed variations below

1 % (four inter-comparisons perfomled between Mru'ch 2005 and June 2010) which guarantees the stabili ty of the global so lru' irradiance data used in this work.

[9] A Cimel CE-318 Still photometer, co-located with the UVB- I and CM-II instruments, makes direct sun measure­ments with a 1.20 fi.1I1 field of view at seven wavelengths between 340 and 1020 nm, at every 15 min. This instrument is paft of the Iberian network for Sun photometer aeroso l measurements (RIMA), a scientific regional network feder­ated to NASA AERONET global network [Holben et aI., 1998]. From the direct sun measurements and using the cal­ibration constants provided by AERONET-RlMA, the aero­so l optical depths (AOD) at seven wavelengths are derived fo llowing the method described in the works of Alados­Arboledas et ai. [2003, 2008] . Furthermore, the inversion procedure of Olmo et al. [2006, 2008] is utilized to retrieve columnar aerosol optical and microphysical properties such as single scattering albedo (SSA). This inversion code uses as input parameters AOD data derived from direct Sun pho­tometer measurements, and sky radiance measurements in the principal plane configuration.

2,2, Satellite Data

[10] The OMI sate llite instrument is on board NASA EOS/ Aura platform launched in July 2004 [Schoeberl et al., 2006). This instrument consists of a nadir viewing push-broom spectrometer that measures solar backscattered radiation in the spectra l range from 270 nm to 500 nm with a resolution of 0.55 nm in the ultraviolet and 0.63 nm in the visib le. The OMI instrument has a 2600 km wide viewing swath and it is capable of daily global contiguous mapping. The footprint size of satellite pixel is 13 by 24 km at nadir increasing up to ~ 150 Ian off-nadir viewing mrections.

[II] The OMI surface UV algorithm (OMUYB) is based on the UV algorithm for Tota l Ozone Mapping Spectrometer (TOMS) instruments developed at NASA Goddard Space Flight Center (GSFC) [Krotkov et al. , 1998, 2001 ). This algori thm estimates surface UV irradiance from lookup tables (LUTs) obtained by a radiative transfer model using the OMI-derived total ozone, surface albedo and cloud infor­mation as input parameters [Tanskanen et al., 2006, 2007).

[12] In this study, the OMUYB product used is OPEDRate (Overpass Erythemal Dose Rate). In addition, OMUYB data set contains the Lambertian Equi valent Refl ectivity (LER) at 360 run wh ich is used for cloud characterization. Additi on­all y, we use the Aerosol Index (AI) calculated from 331 n.m and 360 nm radiances which gives information about absorbing aeroso ls. All these OMI products are downloaded from tbe Aura Validation data Center site at http ://avdc.gsfc. nasa.gov for the OMI station overpass data .

3. Methodology

[13] The inventory of Saharan desert dust events occurred at Granada from 2006 to 20 lOis based on a published methodology using synthetic information fro m models, back-trajectorie rulalysis, synoptic meteorological charts, satellite retrievals and surface data. Detailed information abo ut this inventory can be fo und in the works of Va lenzuela et al. [201 2a, 20 12b] who evaluated Saharan dust aerosol optical properties and its dependence on source region and transp0l1 pathways.

20f8

Dl9209 ANTON ET AL.: DESERT DUST EFFECTS ON UV IRRADlANCE Dl9209

~ ~

(J)

OJ 0

t) c:

'" ::: ·E CX)

'" 0 • c:

'" t= A a: • W r-.. •• • > 0 • ::J • •

<D • 0

to 0

0.0 0.5 1.0 1.5

AODs at 380 nm

Figure 1. Atmospheric transmittance in the UV erythemal spectral range as a functi on of aeroso l optica l depth at 380 nm in the slant path (A ODs) fo r so lar zenith angles small er than 60°. The solid exponential curve represents the values given by equation (3).

[14] In this work, the dust effect on the UVER is described in terms of the relative aeroso l transmi ttance (T UVER), rela­ti ve to no-aerosol clear sky UNER 0 [Krolkov el at., 1998]:

T _ UVER UVER - UVERo ( I)

In this express ion UVER represents the erythemal mea­surements recorded dwi.ng desert dust intrusions, and UVERo corresponds to the erythemal data for the same solar zeni th angle (SZA) estimated from the empirical expression [Madron ich, 2007]:

o b (TOC) C UVER == Cl (J.to ) 300 (2)

where ~LO is the cosine oftbe SZA and TOe is the total ozone column in Dobson Units (DU) provided by the OMI satellite instrument (OMT03 product using ASA TOMS V8 retrieval algorithm [Bharlia and Wellemeyer, 2002]). Th is parameterized radiative model can be adjusted llSing avail­able experimental data, at the loca l site [Koepke el af. , 1998 ]. Anion el al. [20 lIb 1 calculated the coefficients (a, b and c) in eq uation (2) fo r Granada site using UVER measurements durin g cleanest air condi tions at the site. They validated this empirical model using measurements collected during a peliod not previously used for ca lcul ating fitti ng coeffi ­cients. The results show a reliability of the empirical model (2), which estimates UVERo with a mean absol ute bias less than 2.5%.

[1 5] Finally, the atmospheric aerosol transmittance is ca l­culated from equation (I) by using measured UVER values averaged within ±2 min of each Cimel AOD retrieval during desert dust events (2006-2010).

[1 6] In order to analyze the effects of desert dust events on OMI-delived swface UV in adiances a single OMI ground pixel most closely collocated with Granada station is selected as the best match for each day . We used OMI pixels with centers from I km to 78 Ian from the study site, with the mean and median values being 17 and 11 km, respectively. Five sUllace UVER measurements within ±2 min from the OMI overpass at rv 13:30 are averaged for compari son with the OMI data. Addi tionally, aerosol information derived from Cimel Sun photometer is averaged between 12:30 and 14: 30 so lar time on each day.

4. Results and Discussion

4.1. Effects on Ground-Based Measurements

[1 7] The mean value (± 1 standard deviation) of the atmo­spheric aerosol transmittance (equation (1 )) is 0.89 ± 0.06 or 11 % average UVER reduction dm-ing desert dust intrus ions over Granada. In rv 12% dust cases UVER decreases more than 20% (T VVER < 0.8), which represents significant reduction in UYER due to aerosol absorption [Krolkov el at., 1998].

[18] Experimental studies about the eva luation of atmo­spheric transmittance in the UV range associated with desert dust ep isodes are very scarce: Dfaz el af. [2007] reported atrnospheric transmittance values between 0.92 and 0.95 for g lobal UV ilTadiance (280-363 nm) measurements in southeastem Spain and Kalashnikova el af. [2007] eva luated the atmospheric transmittance at 340-380 ruTI during 2 dust events in Australia, showing values larger than 0.90. These studies are focused on specific short-term dust events, while our study is based on a long-telm inventory of dust episodes. Figu re I shows measured UYER transmittance (T UVE~ as a function of AOD at 380 nm in the slant path (AODs) for solar zen ith angles (SZA) less than 60°. This var iable takes into account the aerosol extinction in the slant co lunm and it i derived by mul tiplying AOD with the air mass factor equal to sec(SZA) for each measurement [Garcia et aI., 2006 ; Kazadzis el at. , 2009]. From this figure, it can be seen that T UV ER decreases as AODs increases, with mini­mum T UVER values around 0.6 for AODs of 1.5 (attenuation of ~40%) which highlights great influence of desert dust on measured UVER values.

[ 19] The T VVER dependence on AOD can be parameter­ized as the exponential expression:

T UVER = exp(-k· AGDs) (3)

where k depends 0 11 aerosol single scattering co-albedo, l -w [Krotkov el aI., 1998]. This parameter has been deri ved from the lineal regress ion analys is between the logaritlml of T UVE R and AODs, resulting in a mean value of 0.29 1 ± 0.008 (R2 rv 0.7). Corresponding curve is shown in Figure I .

[20] Krotkov et al. [1 998] used a radiative transfer model to obtain the parameter k for different aerosol models. For non-absorbing aeroso l (e.g., anthropogeni c sulfa te), they showed k va lues less than 0. 15. Such sma ll k values (i.e., T UVER rv 1-2% fo r AOD == 0.1) are explained by the mutually compensating effects between the reduction of the direct flux by aeroso l extinction and cOITesponding increase of the d iffuse flux by aerosol scattering. For two dust

3 of 8

DI9209 ANT6N ET AL.: DESERT DUST EFFECTS ON UV IRRA DIANCE Dl9209

a '" (')

a 0 (')

0

N U)

'" < E ~ 0

0 .s '" a: ill 0 > ~ ::>

~ 0 0

;:

0 U)

0

0

• Desert dust events • Clear- sky cases

• •

50 100 150 200 250 300 350

Ground- Based UVER (mW/m"2)

F igure 2. Correlation between OMI and ground-based UVER data for desert dust cases under cloud-free satellite pixels (in red) . Subset of data fo r pristine (clear-sky) cases under cloud- and aerosol-free conditions are shown in gray. The study period is between January 2006 and December 20 I O. The soLid black line is the zero bias line, un it slope.

models, the authors showed that the k values are substan­tially higher (between OJ and 0 .6 for more absorbing dust). The larger k values can be explained by strong absorption of UV radiation by the mineral compounds of the desert dust such as hematite and goethite [Horvath, 1993; Alfaro et al. , 2004) . The lower k '" 0.3 va lue reported in our work com­pared to Krotkov el at. [1 998) simulations can be exp lained by the location of our site thousand kilometers away fro m the desert dust source. Long-range transport of desert dust results in aging and mix ing with other aeroso l types leading to modifica tion of its optical properties [Bauer el at. , 20 II ). Recent ly, Rodriguez et al. [20 11) have shown that anthro­pogenic emissions fi·om crude o il refineries and power plants, located in North African industrial areas, contrib ute to desert dust mixing with other type of particles.

4.2. Dust Etlects 011 Satellite Data

[21) OMI surface UV algorith m as urnes that clouds and aerosols are non-absorbing and, therefore, the sate llite­delived surface UV ilTadiances are expected to show over­estimati on for regions that are affected by absorbing aeroso ls such as smoke or desel1 dust [Tanskan.en et af., 2007).

[22) The variabi lity of cloudiness w ithin the OMI p ixel (13 by 24 km for nadir viewing) can lead to significant dif­fe rence between ground-based and satell ite deli ved UVER data [Weihs el aI. , 2008; Anion et aI. , 2010) . To study the influence of desert dust aerosols on OMI UVER data, pre­dominantly cloud-free pixe ls sbould be considered in the analysis. We use OMI measured Lambertian Equivalent reflectivity (LER) values as proxy for cloud contaminated OMI scenes [Krolkov el aI , 200 1]. Specifica lly, we rej ect satellite scenes with LER va lues larger than 0.1 (Kalliskata el at. , 2000) . F igure 2 shows the relati onship between OMI retrieved and measured UVER data for desel1 dust events

detected at Granada under cloud-free cond itions (LER < 0.1 ). The number of cloud-free days analyzed is 75 (69% of all dusty days) . It can be seen that the correlation between satellite and ground-based UVER data is good (R 2

'" 0.95), but a strong bias is also evident. The mean bias error (MB E) calculated as the average of the relative differences between OMI and measured UV.ER data (UVERoM I_UVER EXP/ UVEREXP) is +22 ± 7% (OMI data be ing higher) where the unceI1ainty is charac telized by the BE standard deviation.

[23] In order to evaluate what part of this large OMI bias can be attributed to the presence of desert dust particles, the relationship between OMI and ground-based UVER data is analyzed for dust-free and cloud-free (i. e., pristine) condi­tions, which we ca U "clear sky." Three diffe rent criteria are simultaneously appli ed for selecting clear sky cases. F irst, LER values smaller than 0 .1 allow identify cloud-fi·ee sat­ellite pixels. Second, the clea.rness index (k,) was used to characterize the atmospheric turbidity during satell ite over­pass. The index is obtained from the ratio of the global solar irradiance to the ex traterrestri al globa l solar irradiance on a horizontal surface [Atadas-Arbotedas el al. , 2000). In order to select cases with low turbidi ty, a conservative thresho ld of k, equal to 0.75 was chosen instead of the value of 0.65 used by other authors [e.g., Kudish et at., 1983; Uda , 2000). This higher threshold guarantees that the selected cases corre­spond to the cleanest air cond itions that occ ur at Granada. The third cri teria was to select those cases with AOD at 440 nm smaller than 0. 1. Thus, we have implicitly assumed in thi s work that tbe atmospheric aerosol detec ted on clear­sky cases is the natura l background . The pairs of satel! ite and ground-based UVER data recorded during clear-sky condi­tions are added to F igure 2. From this plot, it is highlighted that OMI bias is substantially reduced dur ing satellite over­pass under clear-sky conditions. Thus, the MB E decreases to (+ 14.2 ± 4. 1)% for these clear cases. On average, desert dust intrusions over Granada cause an increase of the OMI bias by addi ti onal 8 percentage points which is mainly related to the fac t that current OMUVB algorithm assumes no ab orbing aeroso ls [Tanskanell el al. , 2007). T he main resu lt of th is assumption is the UVER overestimation due to the neglected aerosol absorption. In addition, since desert dust particles also reduce backscatter radiation reaching the sa t­ellite, the OMI algorithm Lmderestimates the effecti ve cloud optica l depth wh ich produces an additional overestimation in UV rad iation products [Krotkov e/ az', 1998, 200 ]). Tbis effective cloud optica l depth is derived fro m matching the measured 360 nm radiance at the OMI overpass time wi th the modeled rad iance assuming non-absorbing C ] cloud layer [Krotkov el aI., 2001). Nevertheless, we would like to point out tbat the analysis fo r clear-sky conditi ons shows a residual positive OMI bias around 14% whi ch is not due to aerosol absorption, but can be related to several SOLU"ces of uncel1a inty both in satelli te and ground-based data.

[24) Several papers [e.g ., Krolkov et aI. , 2005 ; Arata el at. , 2005, 2009; la/ongo et af. , 2008; Kazadzis el al. , 2009; Cachorra el al. , 20 I 0) have used the column aeroso l absorp tion optical depth (AAOD) to quantify the error in the OMI UVER product due to the omission of correction fo r absorbing aerosols in the CWTent OMI UV algorithm. This variable is ca lculated from the following expression:

AAOD(A) = AOD(A) . [I - SSA (A)], (4)

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Dl9209 ANT6N ET AL.: DESERT DUST EFFECTS ON UV IRRADlANCE D1 92 09

• • •

co o

0 .00 0.02 0.04 0.06 O.OB 0 .10

AAOD al31 a nm

Figure 3. Ratio of OMI to ground-based UVER data as a fun cti on of the aerosol absorpti on optical depth (AAOD) extrapolated to 310 run from Cimel values at 440 nm and 870 nm using Absorbing Angstrom Exponent for desert dust cases detected between January 2006 and December 2008. The solid line represents the regression line, with the slope of the fit b = 2.69 (b parameter in equation (6».

where SSA is the single scattering albedo which can be retrieved from the sky radiance measured by the Cimel Sun photometer at 440, 675, 870 and 1020 nm [Olmo et al., 2006, 2008] or direct to diffuse in adiance ratio measured by UV-MFRSR [Kratkov et a f. , 2005]. .

[25] For the OMI bias correction it is necessary to obtam the AAOD at UV wavelengths that are not currently mea­sured with Cimel data. In order to estimate AAOD at 3 10 nm, we use the fo llowing power law wavelength dependence [Bergstrom et aI. , 2007]:

(5)

where AAE is the Absorption Ang trom Exponent wllicb has been derived fro m the AAOD at 440 and 870 run.

[26J Figure 3 shows the ratios of OMI to grOlUld-based UVER data plotted against AAOD at 3 10 run esti mated using equation (5). A ll dusty cloud-free data recorded fo r the period January 2006-December 2008 are included in this plot. It can be noti ced that the ratio increases With lI1creasmg AAOD, confi rming that dust aeroso l absorption can partially ex plain positive OMI UVER bias found in the sate ll ite­ground-based comparison. The regression analysis p rovides a slope of the fit of 2. 1 ± 0.4, indicating the way in which the OMI bias increases wi th an increasing amount of aeroso l absorption. Additionally, the linear least squares fi t shows an intercept value of 1.14 ± 0.02 which correspo nds to the remaining bias under pristine cloud- and aeroso l-free con­ditions. This value suggests that OMI UVER data are biased 14% high compared to the ground-based measurements for clear sky cases .

[27] Based on the above results, OMI UVER data can be post-corrected using tile expression proposed by Krotkov et a f. [2005]:

UVEROM1 . UVER OMI = aperallOllai

corr ( l +bAAOD)' (6)

where the denominator accounts for the presence of absorbi ng aerosols during OMI overpass tinle, with b being tile slope of the regression analysis perfonned in the previous paragraph.

[28] Figure 4 shows the relationship between the reference ground-based UVER measurements and corrected OMI data for an independent data set con·esponding to the period January 2009-December 201 0 (not previously used for cal­culating the b parameter). It can be seen that cOITecti on method produces a clear reduction of the OMI bias. Thus, the MBE decreases from (+2 1 ± 5)% for operational satellite data to (+ 13 ± 4)% for corrected data, slightly smaller than the bias obtained for clear sky conditions (14%) which shows tl1e level of improvement tl13t may be reached with the off-Line correction methodology.

[29] For the off-line aerosol correction of the OMI UV data, Arala et a f. [2009] used the equation (6) with b parameter equal to 3 and monthly AAOD values from the global aerosol climatology of K inn.e [2009]. The improve­ment in ilie OMI UV that can be achieved with this correction has been a lso evaluated by comparing with expelimental UVER data recorded at Granada for ilie period January 2009-December 20 I o. The MBE (+ 13 ± 5)% is close to the bias obtained Witil the correction meiliod used in our work, but with a larger standard deviation. Therefore, the Arola 's correction method could be successfully appli ed to post correct operational OMI UV products over geographical

0

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~ 0 0

0

0

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• Operational OMI • Corrected OMI

• •

50 100

.\

. ,,,i-~~".... .. ., .. --. -

150 200 250

Ground- Based UVER (mW/m"2)

300 350

Figure 4. Correlation between OMI and ground-based DYER data for evaluation data set: deseli dust cases detected between January 2009 and December 20 10. Opera­tional satellite data are in red and corrected satelli te data in gray. The solid black line is th e zero bias line, unjt slope.

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019209 ANTON ET AL.: DESERT DUST EFFECTS ON UV lRRADIANCE 019209

regions where experimental aerosol measurements are not available. This correction is expected to be implemented i.n the next re-processing of the OMI data set.

[30J The predecessor of the satelli te OMI instrument was the TOMS instrument whose archi ved UV products were in fact corrected for aerosol absorption effects (dust and car­bonaceous pruticles) [Krotkov et aI. , 1998]. This correction was applied for those aerosol cases, identified from the TOMS measurements: a combination of the Aerosol Index (AI) larger than 0.5 and the LER less than 0. 15. Thus, the AI = 0.5 is the threshold value chosen by TOMS UV algorithm to distinguish between absorbing and non-absorbing aeroso l in the free troposphere. Contrary to the TOMS UV products, the current surface UV OMI algorithm does not use any con'ection for absorbing aerosols [Tanskanen et al. , 2007]. For the 75 dusty cloud-free days selected in our work, the AI given by OMI is larger than 0.5 in 56 days (75%) which indicate that this satellite product may provide better infor­mation about the absorbing properties of the aerosol load in each pixel. However, the ratio satellite/ground-based UVER data presents a poor correlation with AI values (plot not shown) suggesting that AI itself is not the best quantity to evaluate the effect of absorbing aerosols on the OMI UV bias . It is better using AAOD (equation (4)) estimated from models [Arala et aI. , 2009] or ground measurements [Krotkov et al., 2005].

5. Conclusions

[31J A long inventory of Sahara desert dust events recor­ded at Granada (Spain) has been used to analyze the influ­ence of this type of particles on broadband surface UV inadiance weighted by erythemal action spectrwn (UVER) as retrieved by satellite (OMI) and measured by grow1d­based instruments.

[32J The presence of deseJ1 dust aerosols over th e study site causes average reducti ons of the DYER by about 11 % with respect to clear-sky cond itions. Reductions larger than 20% are found in 12.5% of all desert cases. These results revea l that the desert dust particles markedly affect the propagation of the UV radiation through the atmosphere.

[33J The DYER data derived from the OM! sate ll ite instrument are biased high compared the ground-based OVER measurements during the desert dust cases with a mean relative difference of 22%. The ana lysis of pri tine, clear-sky cases shows that 8% ofthe bias can be attributed to the fac t that current OMI UV algorithm assumes no absorbing aerosols. Therefore, the effect of desel1 dust events on the UV irradiance derived from the OMI instJU­ment CrullOt be neglected for regions like southern Spain, where the intrusions of the deseJ1 dust are frequent.

[34J The aerosol absorption bias can be corrected off-line. The post-correction has been tested using an independent data set and resulted in reduction of the bias from ~21 % for operational satelli te UVER data to ~ 13% fo r corrected data. The remaining positive bias (OMI being higher), indicate additional sources for discrepancy .

[3SJ Thus, OMI -der ived DYER data have been shown to be overesti mated in Iqcations affected by desert dust. Therefore, reliable estimates of UV in these locations are dependent on the availabili ty of quali ty assured grollnd­based measurements.

[36] Ack nowledgments. Manuel Anton thanks M inisterio de C iencia e lnnovaci on and Fonda Socia l E uropeo for th e award ofa postdoctoral grant (Ramon y Cajal) . This work was parti ally supported by the Andalusian Regiona l Govemment through proj ects P08-RNM-3568 and PI O-RNM-6299, the Ministcri o de C iencia e Innovacion through projects CGL2008-059J9-COJ -03/CU, CGL20 10- 18782, CGL-201 '-2992-1 -C02-0 1 and CSD2007--D0067, and by European Uni on through ACTRIS project (E U fNFRA-20 I 0- 1. 1.16- 262254). Nicko lay Krotkov acknow ledges support from NASA Earth Science Division.

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